Absolute Membrane Potential Recording with ASAP-Type Genetically Encoded Voltage Indicators Using Fluorescence Lifetime Imaging
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The electrical membrane voltage ( V m ) characterizes the functional state of biological cells, thus requiring precise, noninvasive V m -sensing techniques. While voltage-dependent fluorescence intensity changes from genetically encoded voltage indicators (GEVIs) indicate V m changes, variability in sensor expression confounds the determination of absolute V m . Fluorescence lifetime imaging microscopy (FLIM) promises a solution to this problem, as fluorescence lifetime is expected to be unaffected by sensor expression and excitation intensity. By examining ASAP1, ASAP3, JEDI-1P, rEstus, and rEstus-NI (G138N:T141I) with one-photon-excited FLIM measurements, we demonstrate that all sensors display a voltage-dependent lifetime. Based on the highest lifetime change in the V m range of −120 to 60 mV, rEstus-NI (798 ps) and ASAP3 (726 ps) are preferred for FLIM recordings. At a physiologically relevant V m of −30 mV, the voltage sensitivity of rEstus-NI (6.6 ps/mV) is 3.6 and 1.4 times greater than that of ASAP1 and rEstus, respectively. As a proof of concept, we successfully used rEstus-NI to estimate absolute resting V m in HEK293T, A375 melanoma, and MCF7 breast cancer cells and quantified spontaneous V m fluctuations in A375 cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".